Nebivolol attenuates oxidative stress and inflammation in a guinea pig model of ovalbumin-induced asthma: a possible mechanism for its favorable respiratory effects
Bibliographic record
Abstract
An experimental model of ovalbumin (OVA) induced asthma was used to assess the effects of nebivolol, the third-generation selective β 1 -adrenergic receptor blocker, on airway reactivity, lung inflammation, and oxidative stress markers. The asthma induction protocol was done by OVA sensitization and challenge. Guinea pigs were classified into control, asthmatic, or asthmatic receiving nebivolol either 7.5 or 15 mg·kg –1 ·day –1 orally. At the end of the study respiratory, the anti-inflammatory and antioxidative effects of nebivolol were assessed. The asthmatic group exhibited a significant increase in early and late airway resistance, airway hyperreactivity to histamine, total and absolute leucocytic count, tumor necrosis factor-α, and interleukin-6 in bronchoalveolar lavage fluid and lung lipid peroxidation and a significant decrease in superoxide dismutase and glutathione compared to the control group. Additionally, there was a significant decrease in lung endothelial nitric oxide synthase (eNOS) and a significant increase in inducible nitric oxide synthase (iNOS) mRNA expression compared to the control group. The high dose of nebivolol counteracted the increased airway resistance induced by OVA, whereas it had no effect on airway hyperresponsiveness. Moreover, nebivolol exhibited significant anti-inflammatory and antioxidant effects and restored the altered levels of eNOS and iNOS compared to the asthmatic group. Collectively, these results suggest a beneficial effect of nebivolol in asthma.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".